Deployment of teams of aerial robots could enable large-scale filming of dynamic groups of people (actors) in complex environments for novel applications in areas such as team sports and cinematography. Toward this end, methods for submodular maximization via sequential greedy planning can be used for scalable optimization of camera views across teams of robots but face challenges with efficient coordination in cluttered environments. Obstacles can produce occlusions and increase chances of inter-robot collision which can violate requirements for near-optimality guarantees. To coordinate teams of aerial robots in filming groups of people in dense environments, a more general view-planning approach is required. We explore how collision and occlusion impact performance in filming applications through the development of a multi-robot multi-actor view planner with an occlusion-aware objective for filming groups of people and compare with a greedy formation planner. To evaluate performance, we plan in five test environments with complex multiple-actor behaviors. Compared with a formation planner, our sequential planner generates 14% greater view reward over the actors for three scenarios and comparable performance to formation planning on two others. We also observe near identical performance of sequential planning both with and without inter-robot collision constraints. Overall, we demonstrate effective coordination of teams of aerial robots for filming groups that may split, merge, or spread apart and in environments cluttered with obstacles that may cause collisions or occlusions.

翻译：空中机器人编队的部署能够实现对复杂环境中动态人群（演员）的大规模拍摄，从而为团队运动与电影摄影等领域的新型应用提供支持。为此，通过顺序贪婪规划实现子模最大化的方法可用于优化编队中机器人的摄像机视角，但这类方法在复杂环境中的高效协调面临挑战。障碍物会产生遮挡并增加机器人间碰撞风险，从而导致近最优性保证的失效条件。为协调密集环境中的空中机器人编队以拍摄人群，需要更通用的视角规划方法。我们通过开发一种具有遮挡感知目标的多机器人多演员视角规划器，探究碰撞与遮挡对拍摄应用性能的影响，并将其与贪婪队形规划方法进行比较。为评估性能，我们在包含复杂多演员行为的五个测试环境中进行规划。与队形规划器相比，我们提出的顺序规划器在三个场景中生成的对演员视角奖励提升14%，在另外两个场景中性能与队形规划相当。我们还观察到，无论是否考虑机器人间碰撞约束，顺序规划的性能几乎一致。总体而言，我们验证了空中机器人编队在人群可能分裂、合并或分散，以及环境存在可能引发碰撞或遮挡的障碍物时，仍能实现高效协作拍摄。